Methodology and Statistics, Tilburg University, Tilburg, The Netherlands.
Statistical Innovation Group, Advanced Analytics Centre, AstraZeneca, Cambridge, UK.
Stat Med. 2018 Jul 30;37(17):2616-2629. doi: 10.1002/sim.7665. Epub 2018 Apr 26.
A wide variety of estimators of the between-study variance are available in random-effects meta-analysis. Many, but not all, of these estimators are based on the method of moments. The DerSimonian-Laird estimator is widely used in applications, but the Paule-Mandel estimator is an alternative that is now recommended. Recently, DerSimonian and Kacker have developed two-step moment-based estimators of the between-study variance. We extend these two-step estimators so that multiple (more than two) steps are used. We establish the surprising result that the multistep estimator tends towards the Paule-Mandel estimator as the number of steps becomes large. Hence, the iterative scheme underlying our new multistep estimator provides a hitherto unknown relationship between two-step estimators and Paule-Mandel estimator. Our analysis suggests that two-step estimators are not necessarily distinct estimators in their own right; instead, they are quantities that are closely related to the usual iterative scheme that is used to calculate the Paule-Mandel estimate. The relationship that we establish between the multistep and Paule-Mandel estimator is another justification for the use of the latter estimator. Two-step and multistep estimators are perhaps best conceptualized as approximate Paule-Mandel estimators.
在随机效应荟萃分析中,有各种各样的研究间方差估计量。这些估计量中有许多(但不是全部)是基于矩方法的。DerSimonian-Laird 估计量在应用中被广泛使用,但 Paule-Mandel 估计量是另一种替代方法,现在也被推荐使用。最近,DerSimonian 和 Kacker 开发了两种基于矩的两步研究间方差估计量。我们将这两种两步估计量扩展为使用多个(两个以上)步骤。我们得出了一个令人惊讶的结果,即随着步骤数的增加,多步估计量趋于 Paule-Mandel 估计量。因此,我们新的多步估计量所基于的迭代方案提供了两步估计量和 Paule-Mandel 估计量之间迄今为止未知的关系。我们的分析表明,两步估计量本身不一定是独特的估计量;相反,它们是与通常用于计算 Paule-Mandel 估计量的迭代方案密切相关的量。我们在多步和 Paule-Mandel 估计量之间建立的关系是后者估计量的另一个理由。两步和多步估计量最好被视为近似的 Paule-Mandel 估计量。